A Deep Learning Approach to Antibiotic Discovery
Jonathan M. Stokes,Kevin Yang,Kyle Swanson,Wengong Jin,Andres Cubillos-Ruiz,Nina M. Donghia,Craig R. MacNair,Shawn French,Lindsey A. Carfrae,Zohar Bloom-Ackermann,Victoria M. Tran,Anush Chiappino-Pepe,Ahmed H. Badran,Ian W. Andrews,Ian W. Andrews,Ian W. Andrews,Emma J. Chory,George M. Church,Eric D. Brown,Tommi S. Jaakkola,Regina Barzilay,James J. Collins +21 more
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TLDR
A deep neural network capable of predicting molecules with antibacterial activity is trained and a molecule from the Drug Repurposing Hub-halicin- is discovered that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens.About:
This article is published in Cell.The article was published on 2020-02-20 and is currently open access. It has received 1002 citations till now.read more
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Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network
TL;DR: Three different deep neural network models (DNN) are developed to predict the antibacterial property of plant metabolites using the fingerprint set of metabolites as features and the first model reduced the number of features where the third model achieved better classification results for test data.
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Reference-free Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network
Xin Shao,Haihong Yang,Xiang Zhuang,Jie Liao,Yueren Yang,Penghui Yang,Junyun Cheng,Xiaoyan Lu,Huajun Chen,Xiaohui Fan +9 more
TL;DR: DeepSort as discussed by the authors is a reference-free cell-type annotation tool for single-cell transcriptomics that uses a deep learning model with a weighted graph neural network, which can reveal cell identities without prior reference knowledge, thus potentially providing new insights into mechanisms underlying biological processes, disease pathogenesis, and disease progression at a singlecell resolution.
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PepVAE3: variational autoencoder framework for antimicrobial peptide generation and activity prediction
TL;DR: PepVAE3 as mentioned in this paper is based on variational autoencoder (VAE) and antimicrobial activity prediction models for designing novel AMPs using only sequences and experimental minimum inhibitory concentration (MIC) data as input.
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Emerging strategies for microbial screening of novel chemotherapeutics
TL;DR: In this paper , the authors provide an overview of various screening approaches to identify new microorganisms, metabolite fingerprinting techniques, and novel chemotherapeutics derived from microbial sources.
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Water-soluble chlorin e6-hydroxypropyl chitosan as a high-efficiency photoantimicrobial agent against Staphylococcus aureus.
TL;DR: In this article , Hydroxypropyl chitosan (HPCS) was employed as a carrier of chlorin e6 (Ce6) through an amide bond to obtain the products with a degree of substitution (DS) ranging from 2.95% to 5.25%.
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